Postvalidation

Postvalidation refers to verification and validation activities conducted after a process, operation, or task has completed. Its purpose is to confirm that the results meet the intended specifications, reconcile output with inputs, and detect issues that may not have been evident during execution. Postvalidation complements pre-validation (checks performed before or during a process) and ongoing validation (checks that occur continuously or in real time).

Applications and scope

Postvalidation is used across domains such as software development, data processing pipelines, financial batch processing, regulatory reporting, and healthcare. In software, it may verify that a release produces correct behavior in the production environment. In data workflows, postvalidation checks data quality, schema conformance, and data integrity after extraction, transformation, and loading (ETL). In finance, it commonly involves reconciliation of settlements, totals, and transaction statuses after batch processing.

Methods and practices

Typical postvalidation activities include automated reconciliation checks, data quality assessments, schema and type verification, consistency checks, anomaly detection, and human review. Generating a post-validation report, maintaining an audit trail, and initiating remediation for detected issues are standard components. The process should define clear acceptance criteria and use independent validation where possible to reduce bias.

Benefits and challenges

Postvalidation improves reliability, traceability, and regulatory compliance by catching errors late in the workflow and providing accountable documentation. Challenges include potential performance overhead, the risk of false positives or negatives, and the need for well-defined criteria to avoid over- or under-verification.

See also

Pre-validation, data validation, quality assurance, post-hoc analysis.